bioRxivEcology
Maximum likelihood estimation of the geometric niche preemption model
Abstract
The geometric series or niche preemption model is an elementary ecological model in biodiversity studies. The preemption parameter of this model is usually estimated by regression or iteratively by using Mays equation. This article proposes a maximum likelihood estimator for the niche preemption model, assuming a known number of species and multinomial sampling. A simulation study shows that the maximum likelihood estimator outperforms the classical estimators in this context in terms of bias and precision. We obtain the distribution of the maximum likelihood estimator and use it to obtain confidence intervals for the preemption parameter and to develop a preemption t test that can address the hypothesis of equal geometric decay in two samples. We illustrate the use of the new estimator with some empirical data sets taken from the literature and provide software for its use.
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- Estimating the fundamental niche: accounting for the uneven availability of existing environmental conditions in the calibration area
L. Jimenez, J. Soberon·bioRxiv·Jan 25, 2021
- Jointly Modeling Species Niche and Phylogenetic Models in a Bayesian Hierarchical Framework
S. W. McHugh, A. Espindola, … J. C. Uyeda·bioRxiv·Jul 6, 2022
- Towards a unification of niche and neutral models of community ecology
Andres Laan, Gonzalo G. de Polavieja·bioRxiv·Feb 28, 2018
- Estimating environmental suitability
J. Drake, R. Richards·EcospherePeer-reviewed·Sep 1, 2018
- Tracking niche change through time: simultaneous inference of ecological niche evolution and estimation of contemporary niches
X. Hua, M. Cardillo, L. Bromham·bioRxiv·Dec 29, 2019
- A Comment On Priors For Bayesian Occupancy Models
J. M. Northrup, B. D. Gerber·bioRxiv·May 17, 2017